Datasets › WebVision › Papers where code ran, page 1

WebVision

Papers archive 2025-07-28

papers with a benchmark row: 51 · with a code link: 37 · where Syntology ran a sample: 16 (11 with a run with no instrument failure, 5 where every run was a failure of Syntology's instrument) Syntology

Show: all papers with a benchmark rowonly where code ran (16 of 51 with a benchmark row: 11 with a run with no instrument failure, 5 where every run was a failure of Syntology's instrument)

Syntology We ran code from the paper's repository; we did not run it on this dataset or check it against this dataset's benchmarks.

Page 1 of 1: papers 1 to 16 of the 16 papers with a benchmark row here where Syntology ran at least one harvested sample (11 with a run with no instrument failure, 5 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.

The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset, not that list; the archive's count for this dataset is 179. The Syntology column is from Syntology's graph, stated per sample; it is not part of any archive number. A line reads “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified” (C is a part of N, never taken away from it); the figure “where Syntology's instrument failed” counts failures of Syntology's instrument, not of the code. “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. When the archive marks a repository official for the paper, the cell starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from. Syntology's record for this page has not changed since , the first build that kept a record date for it; when this build read Syntology's graph is in the build record.

PaperCodeResultsDateSamples run Syntology
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels 1 1 31 May 2023 official (archive's flag): 7 ran · 7 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels 1 1 29 Jul 2022 official (archive's flag): 6 ran · 6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 3 unverified (3 pointer-only for licence)
Selective-Supervised Contrastive Learning with Noisy Labels 1 1 8 Mar 2022 official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (1 pointer-only for licence)
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep Learning 1 3 11 Feb 2022 official (archive's flag): 2 ran · 2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified (3 pointer-only for licence)
Learning with Neighbor Consistency for Noisy Labels 1 5 4 Feb 2022 official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels 1 1 10 May 2021 official (archive's flag): 4 ran · 4 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified (5 pointer-only for licence)
Faster Meta Update Strategy for Noise-Robust Deep Learning 1 1 30 Apr 2021 official (archive's flag): 2 ran · 3 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified (7 pointer-only for licence)
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels 1 1 25 Mar 2021 official (archive's flag): 6 ran · 6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 1 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified
FINE Samples for Learning with Noisy Labels 1 1 23 Feb 2021 official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 2 unverified (7 pointer-only for licence)
Noisy Concurrent Training for Efficient Learning under Label Noise 2 1 17 Sep 2020 official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified
Webly Supervised Image Classification with Self-Contained Confidence 4 1 27 Aug 2020 official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified
Early-Learning Regularization Prevents Memorization of Noisy Labels 2 1 30 Jun 2020 official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified
Normalized Loss Functions for Deep Learning with Noisy Labels 4 2 24 Jun 2020 official (archive's flag): 9 ran · 9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels 3 1 13 May 2019 official (archive's flag): 2 ran · 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (3 pointer-only for licence)
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels 5 1 18 Apr 2018 community repositories only · 7 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 6 where Syntology's instrument failed) · 0 unverified (7 pointer-only for licence)
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach 2 1 13 Sep 2016 official (archive's flag): 1 ran · 2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (2 pointer-only for licence)